Software that Learns from its Own Failures
Document type :
Pré-publication ou Document de travail
Title :
Software that Learns from its Own Failures
Author(s) :
Monperrus, Martin [Auteur]
Université de Lille, Sciences et Technologies
Self-adaptation for distributed services and large software systems [SPIRALS]
Université de Lille, Sciences et Technologies
Self-adaptation for distributed services and large software systems [SPIRALS]
HAL domain(s) :
Informatique [cs]/Génie logiciel [cs.SE]
English abstract : [en]
All non-trivial software systems suffer from unanticipated production failures. However, those systems are passive with respect to failures and do not take advantage of them in order to improve their future behavior: they ...
Show more >All non-trivial software systems suffer from unanticipated production failures. However, those systems are passive with respect to failures and do not take advantage of them in order to improve their future behavior: they simply wait for them to happen and trigger hard-coded failure recovery strategies. Instead, I propose a new paradigm in which software systems learn from their own failures. By using an advanced monitoring system they have a constant awareness of their own state and health. They are designed in order to automatically explore alternative recovery strategies inferred from past successful and failed executions. Their recovery capabilities are assessed by self-injection of controlled failures; this process produces knowledge in prevision of future unanticipated failures.Show less >
Show more >All non-trivial software systems suffer from unanticipated production failures. However, those systems are passive with respect to failures and do not take advantage of them in order to improve their future behavior: they simply wait for them to happen and trigger hard-coded failure recovery strategies. Instead, I propose a new paradigm in which software systems learn from their own failures. By using an advanced monitoring system they have a constant awareness of their own state and health. They are designed in order to automatically explore alternative recovery strategies inferred from past successful and failed executions. Their recovery capabilities are assessed by self-injection of controlled failures; this process produces knowledge in prevision of future unanticipated failures.Show less >
Language :
Anglais
Collections :
Source :
Files
- http://arxiv.org/pdf/1502.00821
- Open access
- Access the document
- 1502.00821
- Open access
- Access the document